Most People Say Social Media Sites Should Crack Down On Harassment, Fake News: Poll

Most People Say Social Media Sites Should Crack Down On Harassment, Fake News: PollAnd just under half of the public says sites aren't doing enough.Most Americans say social media giants have a responsibility to tamp down on online harassment, hate speech and the spread of fake news ― and nearly half say such sites are not doing enough, a new HuffPost/YouGov survey finds.

Two-thirds of Americans say sites such as Facebook, Twitter and YouTube have a responsibility to prevent users from harassing others, and 65 percent say the sites are responsible for preventing people from posting racist content or hate speech. A slightly slimmer majority, 59 percent, say the sites have a responsibility to stem the spread of conspiracy theories or fake news.

But 48 percent of the public says these sites aren’t currently strict enough in regulating what’s posted to them. Fifteen percent say the sites’ current approach is about right, and 12 percent say it’s too strict. One-quarter of respondents say they aren’t sure.

Views vary substantially along political lines. People who voted for Hillary Clinton in the last election are more than twice as likely as President Donald Trump’s supporters to think social media outlets are too lax in regulating content.

Broader views about online dialogue vary as well. Trump voters are just as likely as Clinton voters to say they’ve faced online harassment. (As Pew Research noted in a comprehensive 2017 report on online harassment, what people consider harassing behavior “is highly contextual and varies from person to person.”) But most Trump voters say they believe offensive online content is taken too seriously, while most Clinton voters say such content is too often excused as not a big deal.

Some questions also show gender divides that persist, even when accounting for politics. Female Clinton voters, for instance, say by a 44-point margin, 72 percent to 28 percent, that it’s more important to make people feel welcome and safe online than to make sure people can speak their minds freely. Male Clinton voters are evenly split. Across the aisle, there’s a more modest difference, with male Trump voters 10 points likelier than female Trump voters to prioritize allowing people to freely speak their minds.

Americans say, 25 percent to 16 percent, that banning Jones from posting is a good decision. But the vast majority, 59 percent, say they’re not sure about the wisdom of the decision or that they don’t even know who Jones is.

Jones’ situation hasn’t widely broken through to the public but many on the right have absorbed the sentiment that conservative views are being targeted. Seventy-seven percent of Trump voters say they believe social media sites are biased in favor of liberal views. There’s not a similar sense of suspicion among their political opponents: Just 13 percent of Clinton voters say they believe sites are biased in favor of conservative viewpoints.

Overall, 28 percent of the public, including a slim majority of Trump voters, say they think banning people from social media outlets constitutes a violation of free speech.

Use the widget below to further explore the results of the HuffPost/YouGov survey, using the menu at the top to select survey questions and the buttons at the bottom to filter the data by subgroups:

The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted Aug. 9-11 among U.S. adults using a sample selected from YouGov’s opt-in online panel to match the demographics and other characteristics of the adult U.S. population.

HuffPost has teamed up with YouGov to conduct daily opinion polls.You can learn more about this project andtake part in YouGov’s nationally representative opinion polling. More details on the polls’ methodology are availablehere.

Most surveys report a margin of error that represents some, but not all, potential survey errors. YouGov’s reports include a model-based margin of error, which rests on a specific set of statistical assumptions about the selected sample rather than the standard methodology for random probability sampling. If these assumptions are wrong, the model-based margin of error may also be inaccurate.Click here for a more detailed explanation of the model-based margin of error.